Objective It describes procedures for designing an analyzing a method comparison experiment for serum albumin(ALB) assay and determining the relative bias between two methods using split patient samples.Method According to the procedure described by the NCCL approved guideline: method comparison and bias estimation using patient samples; 40 patient samples were analyzed in 5 operating days, analyze each patient sample in duplicate using both BCG and BCP method. The duplicates were assessed for each method within the same run. The coefficient of correlation was calculated as well as the bia between the methods.Results In the patient′s serum sample, the bias between BCG and BCP methods were 1.8% at 50g/L or 5.5% at 40 g/L or 11.6% at 30 g/L for albumin. In the commercial quality control serum products, the bias between the two methods varied up to 36%.Conclusion In determination of the patient′s ALB, the bias between BCG and BCP goes up when the concentration of ALB is decreased. But the bias between the two methods varies up to 36% when the quality control serum is determined.

Key factors for interpreting proficiency testing (PT)/external quality assessment (EQA) results are knowledge of the commutability of the samples used and the process used for target value assignment.A commutable PT/EQA sample,which would be seen as patients' samples,has the agreement of results among different measurement procedures and demonstrates the same numeric relationship.The value assignment for the sample can be done by using of a reference measurement procedure.Its results can be used to assess the accuracy against a reference measurement procedure or a designated comparison method.Noncommutable PT/EQA samples frequently have a matrix-related bias of unknown magnitude,and can't give meaningful information about the relationship of results for patients' samples among different measurement procedures.Its results must be compared to the peer group mean or the median of results from participants who use measurement procedures that are expected to have the same or very similar matrixrelated bias.

Objective To investigate preanalytical and intraindividual biological variations of 19 biochemistry analytes. Methods For the study of preanalytical variations, 10 consecutive blood specimens were taken from each of 21 individuals and the specimens were taken from different arms and with various evacuated blood tubes and venous occlusion durations and processed with different storages before and after centrifugal separation of serum. Another 3 aliquots of blood, each at an interval of 1 week, were taken from the individuals for the study of intraindividual biological variations. All the serum samples were analyzed in duplicate for 19 biochemistry analytes. Analysis of variance was performed on the results for the estimation of preanalytical and biological variations. Results Various preanalytical treatments or factors caused some systematic variations but random specimen errors were the main contributors of preanalytical variations. Chloride, sodium and calcium showed preanalytical variations of less than 1% and other analytes ranging from 1%-7%. Different analytes showed varied intraindividual biological variations. The least biological variations ( <2% ) were observed on chloride, sodium and calcium and the largest ( >20% ) on bilirubin,triglycerides, alanine aminotransferase and creafine kinase. Conclusions Preanalytical variations under laboratory settings in China and intraindividual biological variations in Chinese for 19 biochemistry analytes have been estimated. These data will be useful in the estimation of measurement uncertainty and the interpretation of clinical laboratory results.

Before performing patient testing with commercial microbial test systems,each laboratory must verify that it can obtain performance specifications comparable to those of the manufacturer.This includes trueness,precision (reproducibility),and reportable range of test results,and verifying that the manufacturer's reference ranges are appropriate for the laboratory's patient population.American Clinical and Laboratory Standards Institute has set up a committeeto develop a verification process and a quality assurance program for commercial microbial identification system and antimicrobial susceptibility testing system,in order to provide recommendations for US Food and Drug Administration (FDA).This guidance is applicable to instrument systems widely used in clinical laboratories and can also be used for manual testing of microbiological identification and antimicrobial susceptibility testing.The aim of this article is to provide advice for the microbial identification system and antimicrobial susceptibility testing system verification process,based on principles of microbiological identification and antimicrobial susceptibility and CLSI M52 guideline.

Objective To retrospectively analyze the literature of alert thresholds for the critical values of clinical biochemistry and hematology tests in adults,and collect the evidence source of these alert thresholds.Methods The literatures during 2006 and 2016 were retrieved,and the evidence sources were evaluated and ranked using the 1999 Stockholm hierarchy for analytical performance specifications in laboratory medicine.Results Thirty most frequently reported laboratory tests with alert thresholds were presented with evidence rankings.Four determination methods of alert thresholds were reported in 92 articles with alert thresholds for critical values.Among them,70％ of alert thresholds were set by individual institutions,18％ by the surveys of clinical laboratories or clinicians,2％ by the recommendation of professional institutions,and 10％ by the evaluation of clinical findings.The sources of these alert thresholds were ranked into level 4,level 3,level 2 and leve 1,respectively.In addition,the alert thresholds of 7 clinical laboratory tests were presented as critical δ values.Conclusion The alert thresholds are set mainly by individual institutions in current clinical laboratoties,followed by the surveys of clinical laboratories or clinicians.Moreover,the general level of evidence source is lower.

In clinical laboratory medicine,measurement uncertainty (MU) is a fixed property of testing results in the measuring system.As an important part of ISO 15189,it is necessary for clinical laboratories to determine MU during the period of validation and verification for each measurement procedure and to review MU over time.Now,testing reports provided by clinical laboratories usually do not offer MU,but some clinical laboratories have already estimated MU in their routine work.Estimation andmonitoring of MU can help clinical laboratories offering more accurate results and provide objective tools for clinicians used in result intcrpretatinn.Generally,result interpretation can be achieved by the result comparison with three main comparators,including a previous result from the same patient,a population reference interval and a clinical decision point.The means of true value and the components contributing to the estimation of MU are both different when the com parison is conducted between testing results and different comparators,so the optimum estimation method of MU is accordingly different,which will subsequently affect the MU value and the determination of clinical decisions.Obviously,depending on the actual clinical uses,laboratories can choose appropriate comparators to the result interpretation and the determination of optimum estimation method of MU.For different clinical uses (diagnosis or monitoring) of the same mearurands,the adoption of different estimation methods should be used to acq uire reasonable MU.By interpreting the concept,characteristics,estimation,and uses of MU,as well as explaining how three main comparison methods of results exploit their own traceable chain to get MU,this paper intends to help clinical laboratories get further understanding of the importancc of MU and provide guidance for the MU estimation in routine work.

Objective To investigate the results of different measuring procedures of hemoglobin A1c (HbA1c) trueness verification scheme in China.Methods Cross sectional survey.The data were collected via the External Quality Assessment (EQA) software from laboratories participated in the First HbA1c trueness verification EQA.Then the collected data were divided into several groups based on laboratory instruments and the data from less than 5 group were excluded.The observed imprecision, bias and sigma (σ) were calculated and the bias％ and CV％ were drew in the sigma chart.The average bias％, CV％ and weighted average σ of each level were also calculated.Results Total 123 laboratories were divided into 9 groups and setting 6％ as the Allowable Total Error, the average bias％, CV％ and weighted average σ of 201411 (target value was 5.4％) were 3.70％, 4.55％ and 0.51 respectively σ, of 201412 (target value was 7.8％)were 2.42％ , 3.56％ and 1.24σ respectively.None of the group achieved the 2σ quality of 201411, and 1 group achieved the 2σ quality of 201412.Conclusions There are obvious biases among the results of many measuring systems and the target value assigned by reference measuring procedures of HbA1c, as well as the imprecision.The Sigma External Quality Assessment Chart is a visual tool, indicating that the quality of measuring systems necessitate improvement therefore to ensure the reliability of results and make better use of HbA1c in clinical application.

Liquid Chromatography-Mass Spectrometry ( LC-MS) is becoming more and more widely used in clinical laboratory ,and LC-MS related quality management requires more rigid than it was .According to CLSI C62-A,this article provides a reference for the validation procedure of LC-MS assay, including limit of detection and lower limit of the measuring interval , linearity and dilution, imprecision, assay interferences and trueness.

Reference materials ( RMs) have been widely used in measurement laboratories , and it is critical to recognise that the material most appropriate for a particular application should be used .Certified reference materials ( CRMs) are used for method validation , the calibration of a measurement system and all other aspects of the evaluation of the measurement system where the trueness of the measurement result is required.For other aspects , such as quality control , precision studies , the checking of the variability between operators , where the results are compared relatively , any suitable reference material can be used . ISO/REMCO, the ISO Committee on Reference Materials , has prepared ISO Guide 80, a guidance document for the in-house preparation of quality control materials ( QCMs ) .QCMs are mostly used to monitor the performance of laboratory methods that have already been validated over time to be able to detect change or when a method goes out of statistical control .QCMs are RMs and have to be sufficiently homogeneous and stable for the intended use.QCMs are usually prepared in-house by laboratory staff for in-house use only , and therefore, the requirements for “in-house” QCMs are less demanding than those for a CRM .The quality assessment of QCMs should involve homogeneity and stability assessments , and a limited characterization of the material to provide an indication of its relevant property values and their variation , prior to use.

In the clinical laboratory medicine,the measurement uncertainty (MU)is a relatively new concept.Over the years, experts of clinical laboratory medicine from all over the world made a great number of further researches and promote the development of MU,which led clinical laboratories to pay more and more attention to the meanings and functions of MU at the same time.However,because of the habitual using of the total error (TE)in clinical laboratories and similarities between concepts of MU and TE which easily resulted in confusion,a lot of laboratories still cannot completely accept MU.By explai-ning concepts of TE and MU and analyzing the pros and cons of models of TE and MU as well as their functions,the obj ec-tive of this paper is to help clinical laboratories make further comprehensions of TE and MU and understand how to properly use them in practice.